Frances Newton appeared on Schwab Network on July 22, 2026, to discuss the evolving artificial intelligence investment landscape and why investors should focus on where the next AI bottlenecks are emerging. She explained that increased competition among AI models does not weaken the long-term investment opportunity but instead expands AI adoption, creating new opportunities across computing, cloud services, and infrastructure.

The conversation explored how AI bottlenecks are shifting beyond semiconductors toward power generation, water, data centers, and other critical infrastructure required to support long-term AI growth. Frances also discussed why infrastructure assets may provide more durable investment opportunities than rapidly changing technology leaders.

She concluded by examining Treasury yields, Federal Reserve policy, inflation, and energy prices, explaining how higher borrowing costs and geopolitical risks could influence both AI-related investments and the broader market outlook.

Key Questions from This Segment

What are AI bottlenecks?

AI bottlenecks are the resources that limit the industry's growth at a given time. While the focus initially centered on advanced chips and memory, the specialized processors and high-speed memory used to train and run AI models, attention is increasingly shifting toward electricity, data centers, cooling systems, water, and network infrastructure needed to support expanding AI demand.

Source: Schwab Network – AI Category

Why is AI infrastructure becoming more important than AI software?

As AI adoption grows, the physical infrastructure required to power, cool, and connect AI systems becomes increasingly valuable. Data centers, electric utilities, transmission networks, and related infrastructure may benefit regardless of which AI models ultimately lead the market, since that infrastructure supports many different AI systems rather than any single one.

Source: Schwab Network – AI Trade Positioning: What's the Next Move

Does increased AI competition hurt AI investments?

Greater competition can reduce costs and improve accessibility, potentially expanding AI adoption. While some technology companies may face pricing pressure, as rivals compete on price to win customers, broader adoption can create opportunities across infrastructure, cloud computing, and enterprise AI services.

Source: Schwab Network – AI Trade Positioning: What's the Next Move

How do Treasury yields affect AI stocks?

Higher Treasury yields, the interest the U.S. government pays on its debt, increase borrowing costs and often place pressure on higher-growth technology companies. That's because a higher yield reduces the present value investors assign to future earnings, since future profits are worth less once discounted back into today's dollars at a higher rate. They can also increase financing costs for large AI infrastructure projects, many of which rely on borrowed money to fund construction.

Source: Schwab Network – Technology Coverage

Why are investors watching energy and power demand for AI?

Modern AI systems require enormous amounts of electricity to operate data centers and train advanced models. As AI deployment expands, reliable power generation and supporting infrastructure, including transmission lines and cooling systems, are expected to remain critical components of the industry's long-term growth.

Source: Schwab Network – AI Bottlenecks Addressed in NVDA Earnings and Ways for Tech to Navigate

Sources: The information above is based on publicly available resources from government agencies and industry organizations. Links are provided for educational purposes to help readers learn more about the topics discussed during this interview. Please note that each link will send you to a different website.

The posted video is a media appearance by Frances Newton on a third-party television program. The views and opinions expressed are those of the speaker as of the date of the broadcast and are subject to change without notice.

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